Computing Science and Mathematics MSc Mathematics and Data Science دراسة University of Stirling في

MSc Mathematics and Data Science

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Mathematics and data science are closely connected. Data science methodologies are built on mathematical principles. Understanding them is crucial for aspiring data scientists (source: Institute of Data 2023). The demand for graduates in this field is growing rapidly fuelled by advances in technology and the increasing importance of data (source: Data Science Jobs 2025). Employers seek individuals with computing skills to manage data and mathematical skills to analyse it. This involves identifying patterns, building models, and making predictions. Our Masters degree in Mathematics and Data Science emphasises the practical application of mathematics for data science. You’ll develop skills that are highly sought after in the data industry. Gain practical maths and data science experience On our Mathematics and Data Science MSc, you get the opportunity to work with academics on commercially relevant research projects. You can also take part in projects with industry or technology providers. Past projects include: Intergen: Data driven forecasting of UK electricity market imbalances Natwest: Building enterprise scale machine learning ops - model monitoring toolkits Scottish National Investment Bank: The decarbonisation of heat in Scotland SportScotland Institute of Sport: Analysis of swimming race data Streamba Ltd: Assessing methods for robust data preparation of heterogeneous sources Eden Court Highlands: Live audience analysis National Records of Scotland: Seasonal adjustment of mortality BBC World Service: Analysis of shifts in political/public opinion using time series analysis and natural language processing tools Learn cutting edge skills which are in demand from employers You'll gain hands on industry standard skills and knowledge from lecturers with research expertise in mathematical modelling, data science and AI. The course covers: statistical analysis of large datasets and data in network form, e.g. social media networks basic and advanced programming using R, Matlab and Python building and analysing mathematical models of real-life systems probability, stochastic optimisation and artificial intelligence data analytics and machine learning relational and non-relational databases cluster computing. Engage with the data science industry This data science and mathematics Masters degree offers a great chance to build your professional network with peers and industry leaders. You’ll benefit from our strong ties with The Data Lab innovation centre who offer networking opportunities. You’ll also engage with industry through guest lectures and local industry career events. Recent speakers include Huawei, Bigspark, Red Star (AI for healthcare), Virtonomy, KBC Group, and Leonardo UK. For students interested in a January start, the course duration is 21 months. For example, students starting in January 2026 will graduate in November 2027.

في أي قسم أنا؟

Computing Science and Mathematics

خيارات الدراسة

دوام كامل (1 عام )

رسوم التسجيــل
£12,150.00 (US$ 15,691) سنوياً
Accommodation(Based on the range of costs for a self-catered room in university halls of residence. Includes cost of electricity and wi-fi.)360.20 to 795.48 (Monthly expenditure)

هذه رسوم ثابتة
تاريخ البدء

سبتمبر 2026

مكان عقــد الدورة

University of Stirling

University of Stirling,

Stirling,

FK9 4LA, Scotland, United Kingdom

دوام كامل (1 عام )

رسوم التسجيــل
£24,300.00 (US$ 31,382) سنوياً
Accommodation(Based on the range of costs for a self-catered room in university halls of residence. Includes cost of electricity and wi-fi.)360.20 to 795.48 (Monthly expenditure)

هذه رسوم مؤقتة قيد القبول
تاريخ البدء

سبتمبر 2027

مكان عقــد الدورة

University of Stirling

University of Stirling,

Stirling,

FK9 4LA, Scotland, United Kingdom

شروط القبول

للطلاب الدوليين

A minimum of a second-class Honours degree, or equivalent, in a numerate subject, e.g. mathematics, physics, engineering, economics; along with some evidence of a mathematical background, such as having taken and passed mathematics modules in at least some of calculus, algebra, statistics and numerical analysis.

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